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Natural Language Processing Capstone

About

Table of contents

  1. Goals of the Course
  2. Project Options
  3. Evaluation
  4. Hardware

Goals of the Course

This class will provide students with an intensive 10-week experience in successfully completing a challenging, well-scoped research project.

Participants will work in small groups (approximately 3 people in each group) to hone their technical skills to quickly absorb and adapt new technical knowledge, gain experience in complex programming, perform thorough experiments and analysis, and learn how to find a path when faced with negative results.

Additional objectives of this class include:

  1. technical communication skills to produce high quality interim technical reports that inspire insightful discussion across project groups,
  2. advisory project experience to provide technical advice and constructive feedback to others, and project management skills to prioritize work items to maximize the chance for successful outcome.
  3. Though not required, some project options in this class have a benefit to the larger community of NLP researchers and practitioners, through the generation of reproducibility reports and open-source artifacts.

Project Options

There are two options for projects:

  1. Reproducibility project (“option R”): reproduce experiments in a recently published NLP paper. Detailed instructions for this option are given here.
  2. Design your own (“option D”). Your team designs a project around something you are interested in. The course staff will do our best to advise you directly or to connect you to local researchers with relevant expertise.

The course calendar details the deadlines for the project’s written reports.

In addition to the written reports, your team is expected to give four five-minute updates over the course of the quarter. Refer to the course calendar for the dates of your team’s updates. You are required to use no more than three slides (including the title slide) for each update. Finally, there will be a final presentation either as a video (which you will upload to Youtube) or as a live poster session at the end of the quarter.

Evaluation

Students will be evaluated as follows:

  1. Reports (ten at 4% each, shared by the team with the exception of reports #5 and #9 which are individual; extra 5% to project proposal and extra 5% to final report)
  2. Five-minute updates (short talks given in lecture; four at 4% each, shared by the team)
  3. Final video or poster presentation (14%)
  4. Feedback to other teams’ reports and presentations (20%)

Your team may use up to three penalty-free late days (total, not per report) for reports #4, #6, #7, and #8. (No late days are allowed for reports #1-3, individual reports #5 and 9, or the final report #10). Work turned in late after the late days are used up will get a zero grade. Feedback to other teams will only count if it is provided within twenty-four hours of their blog post or in-class presentation.

Hardware

Hosts “nlpg00” through “nlpg03” are available for your use this quarter. Each has two NVIDIA GPUs. The /tmp and /local1 folders on each machine are available for student use, and you need to be mindful of cleaning up after yourself.

We hope to provide some Google cloud credits as well; more details when available.